Search results

The purpose of this paper is to examine the quality of the turned surface. The quality of the surface produced depends on the nature of the chips, which are produced while turning metal matrix composites. This quality is a function of the machining parameters, tool material, tool configuration and elements of the composites.

In this study, the turning of AA7075/15 wt.% SiC (particle size 20–40 µm) composites is investigated. Thirty experiments were conducted, and the chip-formation mechanism in turning AA7075/SiCp composites at various combinations of cutting speeds, feed and depth of cuts was studied.

It is observed from the response surface methodology-based experimentation that in turning of coarser reinforcement (particle size 20–40 µm) composites, total gross fracture occurs. This causes small slices of chips and a higher shear plane angle. The nature of chips produced at various combinations of cutting speeds, feed and depth of cuts is different. The chips generated were segmented, spiral in cylindrical form, connected C type, chips with saw tooth, curled chips, washer C type chips, half-curved segmented chips and small-radii segmented chips.

The novelty of this research is that, so far, very little work has been published on the detailed analysis of chips produced during turning of AA7075/15 wt.% SiC (particle size 20–40 µm) composites.

The purpose of this paper is to develop a leakage model of metallic static seals, which can be used to accurately predict the leakage rate and study the corresponding seal characteristics. The metallic static seal is effectively applied to severe rugged environments where conventional seals cannot meet the needs. More research efforts for deepening the understanding of its seal characteristics are important for its effective and safe applications, of which the study about its leak is one key component.

In the microscopic observations of the turning surface that is general in the processing of flange surfaces, it is found that the spiral morphology is dominant, which had been also obtained by other researches. There are two potential leakage paths for the flange surface of spiral morphology, one is the radial direction perpendicular to the spiral ridges and the other is the circumferential direction along the spiral groove. Based on the microgeometry characteristics of spiral morphology, the micromorphology of turning flange surface is simplified for the calculation of leakage rate, and the simplified methods of the radial and circumferential leakage paths are presented separately. The topography of flange surface studied in this paper is actually measured, and the Abbott bearing surface curve is adopted to represent the micro-profiles parameters. The radial and circumferential leakage models are further developed based on the assumption of laminar flow of the viscous compressible gas.

The experiments used to verify the leakage models were carried out, and the experimental values are well agreed with the calculated values. As the contact pressure increases, the change rules of both radial and circumferential leakage rates are obtained and the obvious transition from radial leak to circumferential leak can be found. Using the proposed leakage models, the effects of the key micro-profiles parameters on the leakage rates are studied, and some specific conclusions are given simultaneously, which are favorable for the theoretical study and practical application of the metallic static seal.

By the interpretations of the micromorphology characteristics of turning flange surface, the leakage mechanism of the metallic static seal is further made clear. The proposed leakage model reveals the relationships between the key micro-profiles parameters and some sealing performances about the leakage and can predict the leakage rates of the metallic static seal used in various working conditions.

For the metallic static seal, the simplification of the radial leakage path and the radial leakage model are put forward for the first time, so the total leakage model can be systematically reported based on the micromorphology characteristics of turning flange surface. The effects of the key micro-profiles parameters on the seal behaviors including of the leak rate, critical contact pressure and transition from radial leak to circumferential leak etc are also clarified firstly.

This research aims to present the characteristics of dimple structure which was fabricated using a turning machine, where the characteristics include sizes, shapes, area ratio and aspect ratio. This research aims at filling the gap in the machining parameters of previous research in producing dimple by using turning process with the aid of dynamic assisted tooling for turning (DATT). In producing dimple, a carbide insert grade H1 was used on a hypereutectic aluminium silicon alloy (A390) material. Dimple has many advantages such as for reducing friction coefficient, load-carrying capacity and trap wear debris for sliding mechanical components.

There are seven machining parameters (cutting speed, feed rate, depth of cut, frequency, amplitude, rake angle, relief angle and nose radius) which have an influence on dimple produced. Taguchi method (orthogonal arrays L8) was used to conduct the experiment systematically and efficiently for these seven parameters. A carbide insert grade H1 was used as a cutting tool on a turning machine with the aid of DATT. The dimple structure was fabricated on a cylindrical rod hypereutectic aluminium silicon alloy (A390). A profilometer 3D Alicona infinite focus and an optical microscope equipped with Vis software were used to analyse the fabricated dimple structure.

Various shapes and sizes of ellipse dimples were produced in this research, including short and long drops with lengths in the range of 517.03–3,927.61 µm, widths of 565.15–1,039.19 µm, depths of 14.46–124.87 µm, area ratios of 5.05–25.65% and aspect ratios of 0.007%–0.111%. There were four experiments within the optimal area ratio range of 10%–20%, i.e. the second, third, seventh and eighth experiments. The width of these dimples was 895.95, 961.39, 787.27 and 829.22 µm, length was 826.26, 3163.13, 885.98 and 1026.65 µm, depth was 83.67, 84.19, 87.05 and 110.70 µm and area ratio was 15.12%, 13.14%, 14.79% and 12.70%. The surface roughness of textured surface was below 1 µm. In this research, the results obtained were similar with that of previous researchers on dimple structure related to tribology performance.

There exists machining parameters, namely, cutting speed and frequency, that were not used by previous research in producing dimple. These machining parameters (cutting speed and frequency) were used in this research to produce dimple via turning process with the aid of DATT using carbide insert grade H1. The turning process is an environmentally friendly process which is suitable for mass production for fabricating dimple structure as compared to most of the current methods which are widely used in fabricating dimple structure.

The present study spotlights the single and multicriteria decision-making (MCDM) methods to determine the optimal machining conditions and the predictive modeling for surface roughness (Ra) and cutting tool flank wear (VB) while hard turning of AISI 4340 steel (35 HRC) under dry environment.

In this study, Taguchi L16 design of experiments methodology was chosen. The experiments were performed under dry machining conditions using TiSiN-TiAlN nanolaminate PVD-coated cutting tool on which Taguchi and responses surface methodology (RSM) for single objective optimization and MCDM methods like the multi-objective optimization by ratio analysis (MOORA) were applied to attain optimal set of machining parameters. The predictive models for each response and multiresponse were developed using RSM-based regression analysis. S/N ratios, analysis of variance (ANOVA), Pareto diagram, Tukey's HSD test were carried out on experimental data for profound analysis.

Optimal set of machining parameters were obtained as cutting speed: at 180 m/min., feed rate: 0.05 mm/rev., and depth of cut: 0.15 mm; cutting speed: 145 m/min., feed rate: 0.20 mm/rev. and depth of cut: 0.1 mm for Ra and VB, respectively. ANOVA showed feed rate (96.97%) and cutting speed (58.9%) are dominant factors for Ra and VB, respectively. A remarkable improvement observed in Ra (64.05%) and VB (69.94%) after conducting confirmation tests. The results obtained through the MOORA method showed the optimal set of machining parameters (cutting speed = 180 m/min, feed rate = 0.15 mm/rev and depth of cut = 0.25 mm) for minimizing the Ra and VB.

This work contributes to realistic application for manufacturing industries those dealing with AISI 4340 steel of 35 HRC. The research contribution of present work including the predictive models will provide some useful guidelines in the field of manufacturing, in particular, manufacturing of gear shafts for power transmission, turbine shafts, fasteners, etc.

Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations.

The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF.

From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance.

Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly.

This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/

This paper presents a study of the development of surface roughness model when turning the mild steel hardened up to 484 HV with mixed alumina ceramic (KY1615) and coated alumina ceramic cutting tools (KY4400). The model was developed in terms of main cutting parameters such as cutting speed, feed rate and depth of cut, using response surface methodology. The established equation indicated that the feed rate affected the surface roughness the most, but other parametres remined stable for arithmetic average height parametre (Ra). However, it decreased with increasing the cutting speed, and with the starting and finishing point of cut for ten point height parametre (Rz). The cutting speed and the depth of cut had a slight effect on surface roughness values of Ra, Rz when using KY4400 cutting tools. Furthermore, the average surface roughness value of Ra was about 0.926 um, 1.089 um for KY1615, KY4400 cutting tools, respectively. The predicted surface roughness was found to be very close to experimentally observed ones at 95% confidence level. Moreover, analysis of variance indicated that squares terms were significant but interaction terms were insignificant for both cutting tools.

Surface roughness, normally defined by the R_a and R_t/R_max parameters, is an important topic in the manufacturing engineering, for controlling produced components. This paper presents a study of the influence of cutting parameters on surface roughness in turning of glass‐fibre‐reinforced plastics (GFRPs). A plan of experiments was performed on controlled machining with cutting parameters prefixed in workpiece. A statistical technique, using orthogonal arrays and analysis of variance, has been employed to investigate the influence of cutting parameters on surface roughness in turning GFRPs tubes using polycrystalline diamond cutting tools. The objective was to obtain the contribution percentages of the cutting parameters (cutting velocity and feed rate) on the surface roughness in GFRPs workpiece.

The purpose of this paper is to explore a multi-criteria decision-making (MCDM) methodology to determine an optimal combination of process parameters that is capable of generating favorable dimensional accuracy and product quality during turning of commercially pure titanium (CP-Ti) grade 2.

The present paper recommends an optimal combination of cutting parameters with an aim to minimize the cutting force (F_c), surface roughness (R_a), machining temperature (T_m) and to maximize the material removal rate (MRR) after turning of CP-Ti grade 2. This was achieved by the simultaneous optimization of the aforesaid output characteristics (i.e. F_c, R_a, T_m, and MRR) using the MCDM-based TOPSIS method. Taguchi’s L₉ orthogonal array was used for conducting the experiments. The output responses (cutting force: F_c, surface roughness: R_a, machining temperature: T_m and MRR) were integrated together and presented in terms of a single signal-to-noise ratio using the Taguchi method.

The results of the proposed methodology depict that the higher MRR with desirable surface quality and the lower cutting force and machining temperature were observed at a combination of cutting variables as follows: cutting speed of 105 m/min, feed rate of 0.12 mm/rev and depth of cut of 0.5 mm. The analysis of variance test was conducted to evaluate the significance level of process parameters. It is evident from the aforesaid test that the depth of cut was the most significant process parameter followed by cutting speed.

The selection of an optimal parametric combination during the machining operation is becoming more challenging as the decision maker has to consider a set of distinct quality characteristics simultaneously. This situation necessitates an efficient decision-making technique to be used during the machining operation. From the past literature, it is noticed that only a few works were reported on the multi-objective optimization of turning parameters using the TOPSIS method so far. Thus, the proposed methodology can help the decision maker and researchers to optimize the multi-objective turning problems effectively in combination with a desirable accuracy.

The purpose of this paper is to realize an effective hybrid modeling (empirical-geometric) in order to describe the real behavior of the average roughness variation of the workpiece surface in turning with an elementary operation of superfinishing, using different analytic methodologies. The previous works are limited to describe the roughness for the usual elementary operations, citing the roughing and the semi-finishing, while this analysis builds technical rails for the industrialists in order to well conduct the operation of superfinishing in turning, by choosing the cutting parameters from the proposed model.

A statistical analysis of the average roughness measurements capability study, by the statistical process control method SPC and the ANN artificial neuron network, Levenberg–Marquardt's methods modified Monte Carlo SRM response surface.

The objective of this work was to describe the average roughness generated by the penetration of the cutting tool into a part in superfinishing turning. First, the authors used artificial colony analysis to determine optimal cutting conditions in order to have an average roughness lower than 0.8 µm. The cutting conditions selected: (1) the feed rate f ϵ [0.05; 0.2] mm/rev; (2) the pass depth ap ϵ [0.25; 1] mm; (3) the corner radius re = 0.2 mm and (4) cutting speed V_c ϵ [75; 100] m/min.

This work consists to realize an effective hybrid modeling (empirical-geometric) in order to describe the real behavior of the average roughness variation of the workpiece surface in turning with an elementary operation of superfinishing, using different analytic methodologies. The previous works are limited to describe the roughness for the usual elementary operations, citing the roughing and the semi-finishing, while this analysis builds technical rails for the industrialists in order to well conduct the operation of superfinishing in turning, by choosing the cutting parameters from the proposed model.

The study has been aimed to search an appropriate process environment for simultaneous optimization of quality‐productivity favorably. Various surface roughness parameters (of the machined product) have been considered as product quality characteristics whereas material removal rate (MRR) has been treated as productivity measure for the said machining process.

In this study, three controllable process parameters, cutting speed, feed, and depth of cut, have been considered for optimizing material removal rate (MRR) of the process and multiple surface roughness features for the machined product, based on L₉ orthogonal array experimental design. To avoid assumptions, limitation, uncertainty and imprecision in application of existing multi‐response optimization techniques documented in literature, a fuzzy inference system (FIS) has been proposed to convert such a multi‐objective optimization problem into an equivalent single objective optimization situation by adapting FIS. A multi‐performance characteristic index (MPCI) has been defined based on the FIS output. MPCI has been optimized finally using Taguchi method.

The study demonstrates application feasibility of the proposed approach with satisfactory result of confirmatory test. The proposed procedure is simple, and effective in developing a robust, versatile and flexible mass production process.

In the proposed model it is not required to assign individual response weights; no need to check for response correlation. FIS can efficiently take care of these aspects into its internal hierarchy thereby overcoming various limitations/assumptions of existing optimization approaches.